Optimal DNA Codes for Computing and Self-Assembly

Optimal DNA Codes for Computing and Self-Assembly

Max H. Garzon (The University of Memphis, USA), Vinhthuy Phan (The University of Memphis, USA) and Andrew Neel (The University of Memphis, USA)
Copyright: © 2009 |Pages: 17
DOI: 10.4018/jnmc.2009010101
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DNA has been re-discovered and explored in the last decade as a “smart glue” for self-assembly from the “bottom-up” at nanoscales through mesoscales to micro- and macro-scales. These applications require an unprecedented degree of precision in placing atom-scale components. Finding large sets of probes to serve as anchors for such applications has been thus explored in the last few years through several methods. We describe results of a tour de force to conduct an exhaustive search to produce large codes that are (nearly) maximal sets while guaranteeing high quality, as measured by the minimum Gibbs energy between any pair of code words, and other criteria. We also present a quantitative characterization of the sets for sizes up to 20-mers and show how critical building blocks can be extracted to produce codes of very high quality for larger lengths by probabilistic combinations, for which an exhaustive search is out of reach.

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